Kather et al. [1]} proposed a two-step deep learning model to predict microsatellite instability (MSI) directly from histology in gastrointestinal cancer. They first detect the tumor regions in a H&E image. Then, train a second CNNs to classify the tumor patches into MSI and MSS. The experimental results on the TCGA data shows the potential of the proposed image-based method against the expensive alternative of the gene expression-based approaches for MSI detection.
